hopefully this helps
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@ -147,7 +147,7 @@ class LocatorSpace:
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)
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)
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if not acceptable_points:
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if not acceptable_points:
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return None, None
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return None, None
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scores = np.sum((self.levels[np.array(acceptable_points).reshape((-1, 1)),
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scores = np.sum((self.levels[np.array(acceptable_points, dtype=np.uint32).reshape((-1, 1)),
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stations]-values)**2, axis=1) / len(stations)
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stations]-values)**2, axis=1) / len(stations)
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best_point = acceptable_points[np.argmin(scores).ravel()[0]]
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best_point = acceptable_points[np.argmin(scores).ravel()[0]]
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